Hemoglobin correction for near-infrared pH determination in lysed blood solutions

The near-infrared (NIR) measurement of blood pH relies on the spectral signature of histidine residing on the hemoglobin molecule. If the amount of hemoglobin in solution varies, the size of the histidine signal can vary depending on changes in either the pH or hemoglobin concentration. Multivariate calibration models developed using the NIR spectra collected from blood at a single hemoglobin concentration are shown to predict data from different hemoglobin levels with a bias and slope. A simple, scalar path length correction of the spectral data does not correct this problem. However, global partial least-square (PLS) models built with data encompassing a range of hemoglobin concentration have a cross-validated standard error of prediction (CVSEP) similar to the CVSEP of data obtained from a single hemoglobin level. It will be shown that the prediction of pH of an unknown sample using a global PLS model requires that the unknown have a hemoglobin concentration falling within the range encompassed by the global model. An alternative method for correcting the predicted pH for hemoglobin levels is also presented. The alternative method updates the single-hemoglobin-level models with slope and intercept estimates from the pH predictions of data collected at alternate hemoglobin levels. The slope and intercept correction method gave SEP values averaging to 0.034 pH units. Since both methods require some knowledge of the hemoglobin concentration in order for a pH prediction to be made, a model for hemoglobin concentration is developed using spectral data and is used for pH correction.     

Blank augmentation protocol for improving the robustness of multivariate calibrations

An updating procedure is described for improving the robustness of multivariate calibration models based on near-infrared spectroscopy. Employing a single blank sample containing no analyte, repeated spectra are acquired during the instrumental warm-up period. These spectra are used to capture the instrumental profile on the analysis day in a way that can be used to update a previously computed calibration model. By augmenting the original spectra of the calibration samples with a group of spectra collected from the blank sample, an updated model can be computed that incorporates any instrumental drift that has occurred. This protocol is evaluated in the context of an analysis of physiological levels of glucose in a simulated biological matrix designed to mimic blood plasma. Employing data of calibration and prediction samples acquired over approximately six months, procedures are studied for implementing the algorithm in conjunction with calibration models based on partial least squares (PLS) regression. Over the range of 1-20 mM glucose, the final algorithm achieves a standard error of prediction (SEP) of 0.79 mM when the augmented PLS model is applied to data collected 176 days after the collection of the calibration spectra. Without updating, the original PLS model produces a seriously degraded SEP of 13.4 mM.     

Raman spectroscopy-based sensitive and specific detection of glycated hemoglobin

In recent years, glycated hemoglobin (HbA1c) has been increasingly accepted as a functional metric of mean blood glucose in the treatment of diabetic patients. Importantly, HbA1c provides an alternate measure of total glycemic exposure due to the representation of blood glucose throughout the day, including post-prandially. In this article, we propose and demonstrate the potential of Raman spectroscopy as a novel analytical method for quantitative detection of HbA1c, without using external dyes or reagents. Using the drop coating deposition Raman (DCDR) technique, we observe that the nonenzymatic glycosylation (glycation) of the hemoglobin molecule results in subtle but discernible and highly reproducible changes in the acquired spectra, which enable the accurate determination of glycated and nonglycated hemoglobin using standard chemometric methods. The acquired Raman spectra display excellent reproducibility of spectral characteristics at different locations in the drop and show a linear dependence of the spectral intensity on the analyte concentration. Furthermore, in hemolysate models, the developed multivariate calibration models for HbA1c show a high degree of prediction accuracy and precision--with a limit of detection that is a factor of ~15 smaller than the lowest physiological concentrations encountered in clinical practice. The excellent accuracy and reproducibility achieved in this proof-of-concept study opens substantive avenues for characterization and quantification of the glycosylation status of (therapeutic) proteins, which are widely used for biopharmaceutical development. We also envision that the proposed approach can provide a powerful tool for high-throughput HbA1c sensing in multicomponent mixtures and potentially in hemolysate and whole blood lysate samples.     

Pure component selectivity analysis of multivariate calibration models from near-infrared spectra

A novel procedure is proposed as a method to characterize the chemical basis of selectivity for multivariate calibration models. This procedure involves submitting pure component spectra of both the target analyte and suspected interferences to the calibration model in question. The resulting model output is analyzed and interpreted in terms of the relative contribution of each component to the predicted analyte concentration. The utility of this method is illustrated by an analysis of calibration models for glucose, sucrose, and maltose. Near-infrared spectra are collected over the 5000-4000-cm(-)(1) spectral range for a set of ternary mixtures of these sugars. Partial least-squares (PLS) calibration models are generated for each component, and these models provide selective responses for the targeted analytes with standard errors of prediction ranging from 0.2 to 0.7 mM over the concentration range of 0.5-50 mM. The concept of the proposed pure component selectivity analysis is illustrated with these models. Results indicate that the net analyte signal is solely responsible for the selectivity of each individual model. Despite strong spectral overlap for these simple carbohydrates, calibration models based on the PLS algorithm provide sufficient selectivity to distinguish these commonly used sugars. The proposed procedure demonstrates conclusively that no component of the sucrose or maltose spectrum contributes to the selective measurement of glucose. Analogous conclusions are possible for the sucrose and maltose calibration models.     

In vivo near-infrared spectroscopy of rat skin tissue with varying blood glucose levels

We have performed in vivo measurements of near-infrared rat skin absorption in the 4000-5000-cm(-1) spectral range (2.0-2.5-microm wavelength) during a glucose clamp experiment in order to identify the presence of glucose-specific spectral information. Spectra were collected during an initial 3-h period where the animal's blood glucose concentration was held at its normal value. The blood glucose level was then increased above 30 mM by venous infusion of glucose and held for 2 h, after which it was allowed to return to normal. Spectra were recorded continuously during the procedure and are analyzed to identify spectral changes associated with changes in glucose concentration. Because the change in absorbance due to an increase in glucose concentration is small compared to changes due to other variations (e.g., the thickness of the skin sample), a simple subtraction of absorbance spectra from the hyperglycemic and euglycemic phases is not instructive. Instead, a set of principal components is established from the euglycemic period where the glucose concentration is constant. We then examine the change in absorbance during the hyperglycemic period that is orthogonal to these principal components. We find that there are significant similarities between these orthogonal variations and the net analyte signal of glucose, which suggests that glucose spectral information is present. The analysis described here provides a procedure by which the analytical significance of a multivariate calibration can be evaluated.     

Prediction of ethylene content in melt-state random and block polypropylene by near-infrared spectroscopy and chemometrics: comparison of a new calibration transfer method with a slope/bias correction method

This paper reports the prediction of the ethylene content (C2 content) in random polypropylene (RPP) and block polypropylene (BPP) in the melt state by near-infrared (NIR) spectroscopy and chemometrics. NIR spectra of RPP and BPP in the melt states were measured by a Fourier transform near-infrared (FT-NIR) on-line monitoring system. The NIR spectra of RPP and BPP were compared. Partial least-squares (PLS) regression calibration models predicting the ethylene (C2) content that were developed by using each RPP or BPP spectra set separately yielded good results (SECV (standard error of cross validation): RPP, 0.16%; BPP, 0.31%; correlation coefficient: RPP, 0.998; BPP, 0.996). We also built a common PLS calibration model by using both the RPP and the BPP spectra set. The results showed that the common calibration model has larger SECV values than the models based on the RPP or the BPP spectra sets individually and is not practical for the prediction of the C2 content. We further investigated whether a calibration model developed by using the BPP spectra set can predict the C2 contents in the RPP sample set. If this is possible, it can save a significant amount of work and cost. The results showed that the use of the BPP model for the RPP sample set is difficult, and vice versa, because there are some differences in the molar absorption coefficients between the RPP and BPP spectra. To solve this problem, a transfer method from one sample spectra (BPP) set to the other spectra (RPP) set was studied. A difference spectrum between an RPP spectrum and a BPP spectrum was used to transfer from the BPP calibration set to the RPP calibration set. The prediction result (SEP (standard error of prediction), 0.23%, correlation coefficient, 0.994) of RPP samples by the transferred calibration set and model showed that it is possible to transfer from the BPP calibration set to the RPP calibration set. We also studied the transfer from the RPP calibration set (the range of C2 content: 0-4.3%) to the BPP calibration set. The prediction result of C2 content (the range of C2 contents: 0-7.7%) in BPP by use of the calibration model based on the transferred BPP spectra from the RPP spectra showed that the transfer method is only effective for the interpolation of the C2 content range by the nonlinear change in the peak intensities with the C2 content.     

Temperature-independent near-infrared analysis of lysozyme aqueous solutions

Digital Fourier filtering is used to produce a temperature-insensitive univariate calibration model for measuring lysozyme in aqueous solutions. Absorbance spectra over the 5000-4000 cm-1 spectral range are collected for lysozyme standards maintained at 14 degrees C. These spectra are used to compute the calibration model while a set of spectra collected at temperatures ranging from 4 to 24 degrees C are used to validate the accuracy of this model. The root-mean-square error of prediction (RMSEP) is 0.279 mg/mL over a tested lysozyme concentration range of 0.036-51.6 mg/mL. The detection limit is 0.68 mg/mL. In addition, multivariate calibration models based on partial least-squares regression (PLS) are evaluated and compared to the results from the univariate model. PLS outperforms the univariate model by providing a RMSEP of 0.090 mg/mL. Analysis of variance showed that both calibration methods effectively eliminate the adverse affects created by variations in solution temperature.     

Scattering and absorption effects in the determination of glucose in whole blood by near-infrared spectroscopy

Optical properties of whole bovine blood are examined under conditions of different glucose loadings. A strong dependency is established between the scattering properties of the whole blood matrix and the concentration of glucose. This dependency is explained in terms of variations in the refractive index mismatch between the scattering bodies (predominately red blood cells) and the surrounding plasma. Measurements in the presence of a well-known glucose transport inhibitor indicate that variations in refractive index mismatch are related to the penetration of glucose into the red blood cells and demonstrate that increased scattering involves the uptake of glucose by red blood cells. Finally, multivariate calibration models are presented for the measurement of glucose in a whole blood matrix. These models are based on near-infrared spectral data collected from 80 different samples prepared from a single whole blood matrix. Calibration studies are performed over the combination, first-overtone, and short-wavelength spectral regions. The best calibration model is generated from combination region spectra, providing a standard error of prediction (SEP) of less than 1 mM over the concentration range of 3-30 mM. The model based on the first-overtone region is slightly degraded but still provides acceptable performance (SEP = 1.20 mM). The model based on the short-wavelength region is further degraded (SEP = 2.53 mM). To rationalize these results, an analysis of the selectivity of the calibration models is performed by computing the glucose net analyte signal. It is established that the models based on the combination and first-overtone regions are dominated by glucose absorption information, while the model computed from the short-wavelength region is based primarily on scattering information. This result provides evidence that absorption information is needed in order to obtain a glucose calibration model with acceptable performance.     

Glucose quantification in dried-down nanoliter samples using mid-infrared attenuated total reflection spectroscopy

The aim of this study was to determine the feasibility of minimally invasive glucose concentration measurement of a body fluid within the physiologically important range below 100 nL with a number of samples such as interstitial fluid, plasma, or whole blood using mid-infrared spectroscopy, but starting with preliminary measurements on samples of simple aqueous glucose solutions. The Fourier transform infrared spectrometer was equipped with a Golden Gate single reflection diamond attenuated total reflection (ATR) accessory and a room-temperature pyroelectric detector. As the necessary detection limits can be achieved only for dried samples within the spectrometric conditions realized by a commercial instrument, the work focused on the optimization of such ATR measurements. We achieved quantification of samples with volumes as low as 7 nL between 10 and 600 mg/dL. The standard error of prediction (SEP) for the concentration range 10-100 mg/dL is 3.2 mg/dL with full interval data between 1180 and 940 cm(-1). The performance of the prediction is given by a coefficient of variation of prediction (CV(pred) ) of 6.2%. When all samples within the whole concentration range are included, the SEP increases to 20.2 mg/dL, and hence the CV(pred) to 10.6% due to a nonlinear signal dependence on glucose concentration. A detection limit for glucose of 0.7 ng with a signal-to-noise ratio of 10 was obtained.     

In vivo, transcutaneous glucose sensing using surface-enhanced spatially offset Raman spectroscopy: multiple rats, improved hypoglycemic accuracy, low incident power, and continuous monitoring for greater than 17 days

This paper presents the latest progress on quantitative, in vivo, transcutaneous glucose sensing using surface enhanced spatially offset Raman spectroscopy (SESORS). Silver film over nanosphere (AgFON) surfaces were functionalized with a mixed self-assembled monolayer (SAM) and implanted subcutaneously in Sprague-Dawley rats. The glucose concentration was monitored in the interstitial fluid of six separate rats. The results demonstrated excellent accuracy and consistency. Remarkably, the root-mean-square error of calibration (RMSEC) (3.6 mg/dL) and the root-mean-square error of prediction (RMSEP) (13.7 mg/dL) for low glucose concentration (<80 mg/dL) is lower than the current International Organization Standard (ISO/DIS 15197) requirements. Additionally, our sensor demonstrated functionality up 17 days after implantation, including 12 days under the laser safety level for human skin exposure with only one time calibration. Therefore, our SERS based sensor shows promise for the challenge of reliable continuous glucose sensing systems for optimal glycemic control.     

一种基于局部回归算法的多组分定量分析方法

文章针对复杂样本吸收光谱重叠或组分之间相互作用导致偏离朗伯一比尔定律的问题提出了一种以灰色综合关联度作为样本相似性判据的多组分定量分析局部回归建模方法,主要内容是对校正集样本的光谱曲线与待测样本曲线进行灰色综合关联度分析,然后以最小预测均方根误差原则选择与待测样本属性相近的样本组成校正子集,最后建立基于校正子集的偏最小二乘回归模型。相比马氏距离方法,灰色综合关联度结合了绝对位置差和变化率两方面因素,能够更为全面的反映样本之间的相似程度。建立实验系统将本方法应用于食用色素苋菜红、胭脂红、柠檬黄和日落黄混合溶液的定量分析中,实验结果表明,该方法优于全局建模方法,尤其在光谱响应与浓度之间的非线性响应段预测精度得到了明显的提升。     

Quantitation of monosaccharide isotopic enrichment in physiologic fluids by electron ionization or negative chemical ionization GC/MS using di-O-isopropylidene derivatives.

The aldonitrile pentaacetate and other derivatives lack ions in the electron ionization (EI) spectra possessing an intact hexose structure and thus must be analyzed by chemical ionization GC/MS in order to study multiple isotopomers. We report methods for quantitation of hexose di-O-isopropylidene acetate (IPAc) or pentafluorobenzoyl (PFBz) esters. These were prepared in a two-step procedure using inexpensive reagents that do not adversely impact the isotopomer structure of the sugar. The acetate derivative possesses an abundant [M - CH3] ion in the EI spectrum which is suitable for quantitative analysis of isotopomers. The negative chemical ionization (NCI) spectrum of the corresponding pentafluorobenzoyl derivative has a dominant molecular anion. Moreover, the PFBz derivative is about 100-fold more sensitive than the acetate, which offers some advantages for analysis of minor hexoses found in plasma. Isotopic calibration curves of [U-13C]glucose are linear over the 0.1-60% tracer/tracee range tested. The useful range for isotopic tracer studies is 25-2500 pmol for EI analysis of the acetate derivative and 0.1-55 pmol for NCI analysis of PFBz derivative (sample amount injected). For most studies where sample size is not limited, EI-GC/MS analysis of the IPAc derivative is preferred. NCI-GC/MS analysis is reserved when sample size is limiting or when studies involve hexoses other than glucose that are normally present at low concentration.     

Bootstrapping in Controlled Calibration Experiments

We consider the determination of an unknown quantity—for example, the concentration of a particular chemical in a given sample or samples—using controlled calibration. Here several samples are prepared with concentrations chosen to cover a required range, and these are used to establish the relationship between concentration and the measured response to an assay method. This relationship is then used to estimate the concentration in the unknown samples from their measured responses. Confidence intervals for the estimated concentrations can usually be calculated by inverting a prediction interval, but in some situations this method becomes intractable. We explore the use of the bootstrap as an alternative in linear, nonlinear, and multivariate controlled calibration, using both simulation and real datasets from the field of immunoassay. We also discuss the alternatives afforded by replication of the design points. The bootstrap is found to be comparable to the standard method in simple situations and is easy to apply even in complex situations in which standard approaches perform poorly or are intractable.     

Calibration-free method to determine the size and hemoglobin concentration of individual red blood cells from light scattering

At present, hemoglobin concentration and the volume of an erythrocyte can be determined from the intensities of light scattered by an individual cell at fixed angular intervals. This method is used in modern hemoglobin analyzers, but it requires calibration of optical and electronic units by certified particles of known size and refractive index. We describe a method that is based on the parametric solution of an inverse light-scattering problem and does not require a calibration procedure. The method is based on the use of parameters of the entire angular light-scattering pattern, called an indicatrix here. These parameters do not depend on the absolute intensity of light scattering. The indicatrix parameters form approximating equations that relate these parameters to the size and the phase-shift parameters of the particle. The applicability of the method is demonstrated by measurement of the indicatrices of individual sphered erythrocytes. The indicatrices of the individual erythrocytes were measured with a scanning flow cytometer at an angular range of from 15 to 55 deg. The volume and the hemoglobin concentration have been calculated by use of the developed method and by fitting of the experimental indicatrices to the indicatrices calculated from the Mie theory.     

Multivariate calibration models for lysozyme from near-infrared transmission spectra in scattering solutions of monodisperse microspheres

The ability to quantify lysozyme is demonstrated for a series of aqueous samples with different degrees of scattering. Near-infrared spectra are collected for two sets of lysozyme/scattering solutions. In both sets of samples, the solutions are composed of lysozyme dissolved in acetate buffer with suspended monodisperse latex microspheres of polystyrene. The diameter of the microspheres is 6.4 microm for the first set and 0.6 microm for the second. For each set, the amount of microspheres range from 0.005 to 0.998 wt %, the lysozyme concentrations range from 0.834 to 28.6 mg/mL, and solution compositions are designed to minimize correlations between the concentration of lysozyme and percentage of microspheres. Near-infrared spectra are collected individually for each set of solutions. Single-beam spectra are collected over the combination spectral range (5000-4000 cm(-1), 2.0-2.5 microm) by transmitting the incident radiation through a 1.5-mm-thick sample that is maintained at 21 degrees C. Partial least-squares calibration models are evaluated individually for each data set both with and without wavelength optimization. Results indicate that models from raw, nonmodified, single-beam spectra are incapable of extracting lysozyme concentration from these highly scattering solutions. Accurate concentration measurements are possible, however, by implementing either a multiplicative scatter correction to the single-beam spectra or by taking the ratio of these single-beam spectra to an appropriate reference spectrum. In addition, digital Fourier filtering of these spectra enhances model performance. The best calibration model in the presence of 6.4-microm microspheres is obtained from multiplicative scatter corrected single-beam spectra over the 4550-4190-cm(-1) spectral range. The mean percent error of prediction (MPEP) and standard error of prediction (SEP) for this model are 2.2% and 0.28 mg/mL, respectively. Likewise, the multiplicative scatter corrected spectra with wavelength optimization provided the best calibration model for the 0.6-microm data set. In this case, the MPEP and SEP are 2.3% and 0.44 mg/mL, respectively. In addition, the ability to predict lysozyme concentrations is evaluated for the situation where the degree of scattering is greater in the predication samples compared to the calibration samples. Differences in the prediction ability are noted between the 6.4- and 0.6-microm data sets.     

Determination of glucose concentration in a scattering medium based on selected wavelengths by use of an overtone absorption band

A method and device for measuring glucose concentration in a scattering medium have been developed. A spectral range of 800-1800 nm is considered for wavelength selection because of its deeper penetration into biological tissue and the presence of a glucose absorption band. An algorithm based on selected wavelengths is proposed to minimize interference from other components. The optimal distance between the light source and the detector for diffuse reflectance measurement minimizes the influence of medium scattering. The proposed algorithm and measuring device are tested with a solution containing milk with added glucose. Glucose concentrations between 0 and 2000 mg/dl are determined with a correlation coefficient of 0.977. We also investigate the influence of concentration variations of other substances such as water, hemoglobin, albumin, and cholesterol when they are mixed in a scattering medium.     

Nondestructive direct determination of heroin in seized illicit street drugs by diffuse reflectance near-infrared spectroscopy

A new method has been developed for the fast and nondestructive direct determination of heroin in seized street illicit drugs using partial least-squares regression analysis of diffuse reflectance near-infrared spectra. Data were obtained from untreated samples placed in standard glass chromatography vials. A heterogeneous population of 31 samples, previously analyzed by a reference method, was employed to build the calibration model and to have a separated validation set. Based on the use of zero-order data for a calibration set of 21 samples, after standard normal variate and quadratic linear removed baseline correction (detrending), in the wavelength range from 1111 to 1647 nm, 8 PLS factors were enough to obtain a root-mean-square error of prediction of 1.3% w/w, with a quality coefficient of 10% for the estimation of the accuracy error in the prediction of heroin concentration in unknown samples and a residual predictive deviation of 5.4.     

Infrared hollow waveguide sensors for simultaneous gas phase detection of benzene, toluene, and xylenes in field environments

Simultaneous and molecularly selective parts-per-billion detection of benzene, toluene, and xylenes (BTX) using a thermal desorption (TD)-FTIR hollow waveguide (HWG) trace gas sensor is demonstrated here for the first time combining laboratory calibration with real-world sample analysis in field. A calibration range of 100-1000 ppb analyte/N(2) was developed and applied for predicting the concentration of blinded environmental air samples within the same concentration range, and demonstrate close agreement with the validation method used here, GC-FID. The analyte concentration prediction capability of the TD-FTIR-HWG trace gas sensor also compares well with the industrial standard and other experimental techniques including GC-PID, ultrafast GC-FID, and GC-DMS, which were simultaneously operated in the field. With the advent of a quantum cascade laser with emission frequencies specifically tailored to efficiently overlap benzene absorption as the most relevant analyte, the overall sensor footprint could be considerably reduced to ultimately yield hand-held trace gas sensors facilitating direct and real-time detection of BTX in air down to low ppb levels.     

On-line near-infrared spectrometer to monitor urea removal in real time during hemodialysis

The ex vivo removal of urea during hemodialysis treatments is monitored in real time with a noninvasive near-infrared spectrometer. The spectrometer uses a temperature-controlled acousto optical tunable filter (AOFT) in conjunction with a thermoelectrically cooled extended wavelength InGaAs detector to provide spectra with a 20 cm(-1) resolution over the combination region (4000-5000 cm(-1)) of the near-infrared spectrum. Spectra are signal averaged over 15 seconds to provide root mean square noise levels of 24 micro-absorbance units for 100% lines generated over the 4600-4500 cm(-1) spectral range. Combination spectra of the spent dialysate stream are collected in real-time as a portion of this stream passes through a sample holder constructed from a 1.1 mm inner diameter tube of Teflon. Real-time spectra are collected during 17 individual dialysis sessions over a period of 10 days. Reference samples were extracted periodically during each session to generate 87 unique samples with corresponding reference concentrations for urea, glucose, lactate, and creatinine. A series of calibration models are generated for urea by using the partial least squares (PLS) algorithm and each model is optimized in terms of number of factors and spectral range. The best calibration model gives a standard error of prediction (SEP) of 0.30 mM based on a random splitting of spectra generated from all 87 reference samples collected across the 17 dialysis sessions. PLS models were also developed by using spectra collected in early sessions to predict urea concentrations from spectra collected in subsequent sessions. SEP values for these prospective models range from 0.37 mM to 0.52 mM. Although higher than when spectra are pooled from all 17 sessions, these prospective SEP values are acceptable for monitoring the hemodialysis process. Selectivity for urea is demonstrated and the selectivity properties of the PLS calibration models are characterized with a pure component selectivity analysis.     

Comparison of the determination of a low-concentration active ingredient in pharmaceutical tablets by backscatter and transmission Raman spectrometry

A total of 383 tablets of a pharmaceutical product were analyzed by backscatter and transmission Raman spectrometry to determine the concentration of an active pharmaceutical ingredient (API), chlorpheniramine maleate, at the 2% m/m (4 mg) level. As the exact composition of the tablets was unknown, external calibration samples were prepared from chlorpheniramine maleate and microcrystalline cellulose (Avicel) of different particle size. The API peak at 1594 cm(-1) in the second derivative Raman spectra was used to generate linear calibration models. The API concentration predicted using backscatter Raman measurements was relatively insensitive to the particle size of Avicel. With transmission, however, particle size effects were greater and accurate prediction of the API content was only possible when the photon propagation properties of the calibration and sample tablets were matched. Good agreement was obtained with HPLC analysis when matched calibration tablets were used for both modes. When the calibration and sample tablets are not chemically matched, spectral normalization based on calculation of relative intensities cannot be used to reduce the effects of differences in physical properties. The main conclusion is that although better for whole tablet analysis, transmission Raman is more sensitive to differences in the photon propagation properties of the calibration and sample tablets.